


"""simple docstring"""



import argparse
from pathlib import Path

import torch

from transformers import OPTConfig, OPTModel
from transformers.utils import logging


logging.set_verbosity_info()
lowercase_							=							logging.get_logger(__name__)
def      UpperCAmelCase     (       _lowercase :   Union[str, Any]	)						-> Dict:


	"""simple docstring"""




	lowerCAmelCase_      							=			torch.load(_lowercase			,   map_location='''cpu'''	)
	if "model" in sd.keys():
		lowerCAmelCase_      							=			torch.load(_lowercase			,   map_location='''cpu'''	)['''model''']

	# pop unnecessary weights
	lowerCAmelCase_      							=			[
	    '''decoder.version''',
	    '''decoder.output_projection.weight''',
	]
	for key in keys_to_delete:
		if key in sd:
			sd.pop(_lowercase	)

	lowerCAmelCase_      							=			{
	    '''decoder.project_in_dim.weight''': '''decoder.project_in.weight''',
	    '''decoder.project_out_dim.weight''': '''decoder.project_out.weight''',
	    '''decoder.layer_norm.weight''': '''decoder.final_layer_norm.weight''',
	    '''decoder.layer_norm.bias''': '''decoder.final_layer_norm.bias''',
	}
	for old_key, new_key in keys_to_rename.items():
		if old_key in sd:
			lowerCAmelCase_      							=			sd.pop(_lowercase	)

	lowerCAmelCase_      							=			list(sd.keys()	)
	for key in keys:
		if ".qkv_proj." in key:
			lowerCAmelCase_      							=			sd[key]
			# We split QKV in separate Q,K,V

			lowerCAmelCase_      							=			key.replace('''.qkv_proj.'''			,   '''.q_proj.'''	)
			lowerCAmelCase_      							=			key.replace('''.qkv_proj.'''			,   '''.k_proj.'''	)
			lowerCAmelCase_      							=			key.replace('''.qkv_proj.'''			,   '''.v_proj.'''	)

			lowerCAmelCase_      							=			value.shape[0]
			assert depth % 3 == 0
			# `SequeuceParallelTransformerBlock` has QKV weight is separated in K,V,Q despite the naming:
			# https://cs.github.com/facebookresearch/metaseq/blob/51871bd73cd04c038f239ea2a26db1d7f6b37927/metaseq/modules/sequence_parallel_transformer_layer.py#L97
			lowerCAmelCase_							,	lowerCAmelCase_							,	lowerCAmelCase_      							=			torch.split(_lowercase			,   depth // 3			,   dim=0	)

			lowerCAmelCase_      							=			q
			lowerCAmelCase_      							=			k
			lowerCAmelCase_      							=			v
			del sd[key]

	return sd
@torch.no_grad()
def      UpperCAmelCase     (       _lowercase :   List[str]			,   _lowercase :   Union[str, Any]			,   _lowercase :   str=None	)						-> List[Any]:


	"""simple docstring"""




	lowerCAmelCase_      							=			load_checkpoint(_lowercase	)

	if config is not None:
		lowerCAmelCase_      							=			OPTConfig.from_pretrained(_lowercase	)
	else:
		lowerCAmelCase_      							=			OPTConfig()

	lowerCAmelCase_      							=			OPTModel(_lowercase	).half().eval()
	model.load_state_dict(_lowercase	)

	# Check results
	Path(_lowercase	).mkdir(exist_ok=_lowercase	)
	model.save_pretrained(_lowercase	)


if __name__ == "__main__":
		lowercase_							=							argparse.ArgumentParser()
		# Required parameters
		parser.add_argument(
		    '--fairseq_path',
		    type=str,
		    help=(
		        'path to fairseq checkpoint in correct format. You can find all checkpoints in the correct format here:'
		        ' https://huggingface.co/models?other=opt_metasq'
		    ),
		)
		parser.add_argument('--pytorch_dump_folder_path', default=None, type=str, help='Path to the output PyTorch model.')
		parser.add_argument('--hf_config', default=None, type=str, help='Define HF config.')
		lowercase_							=							parser.parse_args()
		convert_opt_checkpoint(args.fairseq_path, args.pytorch_dump_folder_path, config=args.hf_config)



"""simple docstring"""



import json
from typing import List, Optional, Tuple

from tokenizers import normalizers

from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_convbert import ConvBertTokenizer


lowercase_							=							logging.get_logger(__name__)

lowercase_							=							{'vocab_file': 'vocab.txt'}

lowercase_							=							{
    'vocab_file': {
        'YituTech/conv-bert-base': 'https://huggingface.co/YituTech/conv-bert-base/resolve/main/vocab.txt',
        'YituTech/conv-bert-medium-small': (
            'https://huggingface.co/YituTech/conv-bert-medium-small/resolve/main/vocab.txt'
        ),
        'YituTech/conv-bert-small': 'https://huggingface.co/YituTech/conv-bert-small/resolve/main/vocab.txt',
    }
}

lowercase_							=							{
    'YituTech/conv-bert-base': 5_12,
    'YituTech/conv-bert-medium-small': 5_12,
    'YituTech/conv-bert-small': 5_12,
}


lowercase_							=							{
    'YituTech/conv-bert-base': {'do_lower_case': True},
    'YituTech/conv-bert-medium-small': {'do_lower_case': True},
    'YituTech/conv-bert-small': {'do_lower_case': True},
}







class    __a						( __snake_case							):
				lowerCamelCase     :       Optional[int]			       =VOCAB_FILES_NAMES
				lowerCamelCase     :       List[str]			       =PRETRAINED_VOCAB_FILES_MAP
				lowerCamelCase     :       str			       =PRETRAINED_INIT_CONFIGURATION
				lowerCamelCase     :       Any			       =PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
				lowerCamelCase     :       List[str]			       =ConvBertTokenizer







				def __init__( self      ,	UpperCAmelCase=None      ,	UpperCAmelCase=None      ,	UpperCAmelCase=True      ,	UpperCAmelCase="[UNK]"      ,	UpperCAmelCase="[SEP]"      ,	UpperCAmelCase="[PAD]"      ,	UpperCAmelCase="[CLS]"      ,	UpperCAmelCase="[MASK]"      ,	UpperCAmelCase=True      ,	UpperCAmelCase=None      ,	**UpperCAmelCase      ,	):

					'''simple docstring'''






					super().__init__(
					    UpperCAmelCase      ,	tokenizer_file=UpperCAmelCase      ,	do_lower_case=UpperCAmelCase      ,	unk_token=UpperCAmelCase      ,	sep_token=UpperCAmelCase      ,	pad_token=UpperCAmelCase      ,	cls_token=UpperCAmelCase      ,	mask_token=UpperCAmelCase      ,	tokenize_chinese_chars=UpperCAmelCase      ,	strip_accents=UpperCAmelCase      ,	**UpperCAmelCase      ,	)

					lowerCAmelCase_      							=			json.loads(self.backend_tokenizer.normalizer.__getstate__()   )
					if (
					    normalizer_state.get('''lowercase'''      ,	UpperCAmelCase   ) != do_lower_case
					    or normalizer_state.get('''strip_accents'''      ,	UpperCAmelCase   ) != strip_accents
					    or normalizer_state.get('''handle_chinese_chars'''      ,	UpperCAmelCase   ) != tokenize_chinese_chars
					):
						lowerCAmelCase_      							=			getattr(UpperCAmelCase      ,	normalizer_state.pop('''type'''   )   )
						lowerCAmelCase_      							=			do_lower_case
						lowerCAmelCase_      							=			strip_accents
						lowerCAmelCase_      							=			tokenize_chinese_chars
						lowerCAmelCase_      							=			normalizer_class(**UpperCAmelCase   )

					lowerCAmelCase_      							=			do_lower_case







				def      lowerCamelCase_     ( self      ,	UpperCAmelCase      ,	UpperCAmelCase=None   ):

					'''simple docstring'''






					lowerCAmelCase_      							=			[self.cls_token_id] + token_ids_a + [self.sep_token_id]

					if token_ids_a:
						output += token_ids_a + [self.sep_token_id]

					return output







				def      lowerCamelCase_     ( self      ,	UpperCAmelCase      ,	UpperCAmelCase = None   ):

					'''simple docstring'''






					lowerCAmelCase_      							=			[self.sep_token_id]
					lowerCAmelCase_      							=			[self.cls_token_id]
					if token_ids_a is None:
						return len(cls + token_ids_a + sep   ) * [0]
					return len(cls + token_ids_a + sep   ) * [0] + len(token_ids_a + sep   ) * [1]







				def      lowerCamelCase_     ( self      ,	UpperCAmelCase      ,	UpperCAmelCase = None   ):

					'''simple docstring'''






					lowerCAmelCase_      							=			self._tokenizer.model.save(UpperCAmelCase      ,	name=UpperCAmelCase   )
					return tuple(UpperCAmelCase   )